464 research outputs found
Respiratory Medication Adherence : Toward a Common Language and a Shared Vision
Part of this work, conducted by E. Van Ganse, has been performed in the context of the ASTRO-LAB project, which received funding from the European Community's 7th Framework (FP7/2007-2013) under grant agreement no. 282593. Teva supported the meeting costs at which the concepts in this paper were discussed by the co-authors and the open access publication fee for this article. The authors had full editorial control over the ideas presented.Peer reviewedPublisher PD
Mapping the Asthma Care Process:Implications for Research and Practice
BackgroundWhether people with asthma gain and maintain control over their condition depends not only on the availability of effective drugs, but also on multiple patient and health care professional (HCP) behaviors. Research in asthma rarely considers how these behaviors interact with each other and drug effectiveness to determine health outcomes, which may limit real-life applicability of findings.ObjectiveThe objective of this study was to develop a logic process model (Asthma Care Model; ACM) that explains how patient and HCP behaviors impact on the asthma care process.MethodsWithin a European research project on asthma (ASTRO-LAB), we reviewed asthma care guidelines and empirical literature, and conducted qualitative interviews with patients and HCPs. Findings were discussed with the project team and respiratory care experts and integrated in a causal model.ResultsThe model outlines a causal sequence of treatment events, from diagnosis and assessment to treatment prescription, drug exposure, and health outcomes. The relationships between these components are moderated by patient behaviors (medication adherence, symptom monitoring, managing triggers, and exacerbations) and HCP behaviors (medical care and self-management support). Modifiable and nonmodifiable behavioral determinants influence the behaviors of patients and HCPs. The model is dynamic as it includes feedback loops of behavioral and clinical outcomes, which influence future patient and HCP decision making. Key evidence for each relationship is summarized to derive research priorities and clinical recommendations.ConclusionsThe ACM model is of interest to both researchers and practitioners, and intended as a first version (ACM-v1) of a common framework for generating and translating research evidence in asthma care
What We Mean When We Talk About Adherence In Respiratory Medicine
The Respiratory Effectiveness Group (REG; www.effectivenessevaluation.org) supported the Expert Adherence Panel Meeting at which many of the concepts presented in this paper were first discussed. REG also supported the manuscript submission costs. ALD, EvG, and MdB have received funding from the European Community's 7th Framework (FP7/2007-2013) under grant agreement no. 282593. Teva supported the meeting costs at which the concepts in this paper were discussed by the co-authors and the open access publication fee for this article. The authors had full editorial control over the ideas presented.Peer reviewedPublisher PD
Prescription of antibiotics and anxiolytics/hypnotics to asthmatic patients in general practice: a cross-sectional study based on French and Italian prescribing data
BACKGROUND Asthma is often poorly controlled and guidelines are often inadequately followed in medical practice. In particular, the prescription of non-asthma-specific drugs can affect the quality of care. The goal of this study was to measure the frequency of the prescription of antibiotics and anxiolytics/hypnotics to asthmatic patients and to look for associations between sex or age and the prescription of these drugs. METHODS A cross-sectional study was conducted using computerised medical records from French and Italian general practitioners' networks. Patients were selected according to criteria adapted from the HEDIS (Healthcare Effectiveness Data and Information Set) criteria. The outcome measure was the number of antibiotics or anxiolytics/hypnotics prescriptions per patient in 1 year. Parallel multivariate models were developed. RESULTS The final sample included 3,093 French patients (mean age 27.6 years, 49.7% women) and 3,872 Italian patients (mean age 29.1 years, 48.7% women). In the univariate analysis, the French patients were prescribed fewer antibiotics than the Italian patients (37.1% vs. 42.2%, p < 0.00001) but more anxiolytics/hypnotics (17.8% vs. 6.9%, p < 0.0001). In the multivariate models, the female patients were more likely to receive antibiotics (odds ratio: 1.5 [1.3-1.7]) and anxiolytics/hypnotics (odds ratio: 1.8 [1.5-2.1]). CONCLUSIONS The prescription of antibiotics and anxiolytics/hypnotics to asthmatic patients is frequent, especially in women. Asthma guidelines should address this issue by referring to other guidelines covering the prescription of non-asthma-specific drugs, and alternative non-pharmacological interventions should be considered
Mixed dyslipidemias in primary care patients in France
Laurent Laforest1, Baishali M Ambegaonkar2, Thierry Souchet3, Vasilisa Sazonov2, Eric Van Ganse11Lyon University, Lyon, France; 2Merck and Co Inc, Whitehouse Station, NJ, USA; 3Merck, Sharp &amp; Dohme, Paris, FranceObjective: To determine the prevalence of single and mixed dyslipidemias among patients treated with statins in clinical practice in France.Methods: This is a prospective, observational, cross-sectional, pharmacoepidemiologic study with a total of 2544 consecutive patients treated with a statin for at least 6 months.Main outcome measures: Prevalence of isolated and mixed dyslipidemias of low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides among all patients and among patients at high cardiovascular risk; clinical variables associated with attainment of lipid targets/normal levels in French national guidelines.Results: At least one dyslipidemia was present in 50.8% of all patients and in 71.1% of high-risk patients. Dyslipidemias of LDL-C, HDL-C, and triglycerides were present in 27.7%, 12.4%, and 28.7% of all patients, respectively, and in 51.0%, 18.2%, and 32.5% of high-risk patients, respectively. Among all subjects with any dyslipidemia, 30.9% had mixed dyslipidemias and 69.4% had low HDL-C and/or elevated triglycerides, while 30.6% had isolated elevated LDL-C; corresponding values for high-risk patients were 36.8%, 58.9%, and 41.1%. Age, gender, body mass index and Framingham Risk Score &gt;20% were the factors significantly associated with attainment of normal levels for &ge;2 lipid levels.Conclusions: At least one dyslipidemia persisted in half of all patients and two-thirds of high cardiovascular risk patients treated with a statin. Dyslipidemias of HDL-C and/or triglycerides were as prevalent as elevated LDL-C among high cardiovascular risk patients.Keywords: cholesterol, triglycerides, dyslipidemias, prevalence, treatment outcome, Franc
Mapping the Asthma Care Process : Implications for Research and Practice
The authors would like to thank the participants to the Respiratory Effectiveness Group Adherence symposium for their comments on the model overview presented during this meeting, members of the ASTRO-LAB consortium for collaborative work on reviewing literature and performing qualitative interviews, and patients and clinicians that shared valuable insights into asthma management during the telephone interviews. The research leading to these results has received funding from the European Community's 7th Framework (FP7/2007-2013) under grant agreement no. 282593.Peer reviewedPublisher PD
Explaining the amount and consistency of medical care and self-management support in asthma : a survey of primary care providers in France and the United Kingdom
Copyright © 2018. Published by Elsevier Inc.Peer reviewedPostprin
Does adherence to inhaled corticosteroids predict asthma-related outcomes over time? A cohort study
Funding: The research leading to these results has received funding from the European Community 7th Framework (FP7/2007-2013) under grant agreement n°282593, and H2020 programme (MSCA-IF) under GA n°706028 for AD during manuscript preparation.Peer reviewedPostprin
Measuring medication adherence in asthma : Development of a novel self-report tool
Funding: This work was supported by European Community’s 7th Framework (FP7/2007-2013); Seventh Framework Programme [HEALTH-F5-2011-282593].Peer reviewedPublisher PD
Correlates of quality of life of pre-obese and obese patients: a pharmacy-based cross-sectional survey
<p>Abstract</p> <p>Background</p> <p>The correlates of quality of life (QOL), as measured by the OSQOL questionnaire were investigated in a convenience sample of overweight patients recruited in pharmacies.</p> <p>Methods</p> <p>A convenience sample of patients with a Body Mass Index ≥ 28 kg/m<sup>2 </sup>were recruited in community-based pharmacies. Baseline characteristics and QOL dimensions (1-Physical state, 2-Vitality-desire to do things, 3-Relations with others, 4-Psychological state) were reported in self-completed questionnaires from which the risk of obtaining a low QOL was assessed for each dimension.</p> <p>Results</p> <p>QOL was inadequate for all dimensions in the 494 patients included in the study (median age = 61, 48% women, 21% professional persons/top executives). Older pre-obese and obese patients were more likely to report impaired physical functioning (OR = 2.02, 95%CI = [1.10-3.70]), but were less severely affected socially (OR = 0.32, 95%CI = [0.15-0.69]). Pre-obese and obese professional persons and top executives showed better physical capabilities (OR = 0.35, 95%CI = [0.15-0.81]) and increased vitality (OR = 0.47, 95%CI = [0.23-0.95]). Overall, men's psychological state was better than females' (OR = 0.46, 95%CI = [0.25-0.82]). A body-mass index ≥ 35 kg/m<sup>2 </sup>was significantly associated with poorer QOL scores on physical, relational and psychological dimensions.</p> <p>Conclusion</p> <p>Our data highlighted the influence of the severity of excess weight, gender, age and socioeconomic status on QOL. These factors should be taken into account when interpreting QOL in pre-obese and obese persons.</p
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